Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6948052 | Information and Software Technology | 2018 | 12 Pages |
Abstract
In particular, the results allow for the following conclusions: (i) factors such as number of commits and files in the pull request may influence the reviewers assignment; (ii) factors regarding the requester profile may influence on reviewer allocation; (iii) the social relationship between requester and reviewer exert influence on pull request evaluation, that is, when the reviewer knows the requester, his or her chances of evaluating such contributions may increase; and (iv) factors such as ownership and locality of pull request artifacts are important predictors for the reviewer. Furthermore, we point out that, besides identifying influence factors related to pull request reviewer, the adopted approach allowed us to quantify the extent of that influence via support, confidence, and lift metrics.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Human-Computer Interaction
Authors
Daricélio M. Soares, Manoel L. de Lima Júnior, Alexandre Plastino, Leonardo Murta,